import argparse

import numpy as np

import pandas as pd

import csv

from pyteomics.fasta import read

import matplotlib.pyplot as plt

from scipy.stats import mannwhitneyu

import sys

plt.style.use('seaborn')

parser = argparse.ArgumentParser('Mann-whitney test')

parser.add_argument('-stain',

help='Path to organisms',

required=True

)

parser.add_argument('-coord',

help='Path to coordinate',

required=True

)

parser.add_argument('-save_way',

help='Path to save fold',

required=True

)

args = parser.parse_args()

print('Starting of analyze ...')

fasta = read(args.stain)

coord = open(args.coord)

read_tsv = pd.DataFrame (csv.reader(coord, delimiter="\t"))

read_tsv = read_tsv.T.drop(0)

Methyla_coordinates = []

for ind in range(len(read_tsv)):

if ind == 0:

continue

Methyla_coordinates.append([int(read_tsv[0][ind]), int(read_tsv[1][ind])])

SB_coordinates = []

SBs = read(args.stain)

SB_dict = {}

for line in SBs:

if 'GCF_000005845.2_ASM584v2' in line.description:

SB_dict[line.description.split()[0]] = {}

SB_dict[line.description.split()[0]]['Coordinates'] = []

if 'SB' in args.stain:

SB_dict[line.description.split()[0]]['Coordinates'].append(int(line.description.split()[3].split(':')[0][1:]))

SB_dict[line.description.split()[0]]['Coordinates'].append(int(line.description.split()[3].split(':')[1][: -1]))

SB_dict[line.description.split()[0]]['Sequence'] = line.sequence

else:

SB_dict[line.description.split()[0]]['Coordinates'].append(int(line.description.split()[2].split(':')[0][1:]))

SB_dict[line.description.split()[0]]['Coordinates'].append(int(line.description.split()[2].split(':')[1][: -1]))

SB_dict[line.description.split()[0]]['Sequence'] = line.sequence

print('Analyzing methylome compaunds ...')

Methylation_sites = []

freq_list_mid = []

freq_list_end = []

for SB in SB_dict:

count_mid = 0

count_end = 0

for coord in Methyla_coordinates:

if SB_dict[SB]['Coordinates'][0] + 150 < coord[0] and SB_dict[SB]['Coordinates'][1] - 150 > coord[1]:

count_mid += 1

elif SB_dict[SB]['Coordinates'][0] < coord[0] and SB_dict[SB]['Coordinates'][0] + 150 > coord[1]:

count_end += 1

elif SB_dict[SB]['Coordinates'][1] - 150 < coord[0] and SB_dict[SB]['Coordinates'][1] > coord[1]:

count_end += 1

if count_mid != 0:

freq_list_mid.append(count_mid)

if count_end != 0:

freq_list_end.append(count_end)

fig, axes = plt.subplots(nrows=1, figsize=(15,8))

axes.yaxis.grid(True)

axes.set_ylabel('Frequency of methylated sites, %')

savefile = open(args.save_way + 'RESULT_METHYLOME_SIBELIA.txt', 'w')

savefile.write('Mann Whitneyu results\tP-value = {}\n'.format(mannwhitneyu(freq_list_end, freq_list_mid)[1]))

savefile.close()

print('P-value = {}'.format(mannwhitneyu(freq_list_end, freq_list_mid)[1]))

plt.boxplot([freq_list_end, freq_list_mid], labels=['END', 'MID'])

plt.savefig(args.save_way + 'BOX_PLOT_METHYLOME_SIBELIA.pdf', format='pdf', dpi=300)

print('Done!')